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CSRID
Published by Universitas Potensi Utama
ISSN : 20851367     EISSN : 2460870X     DOI : https://doi.org/10.22303/csrid
Core Subject : Science,
Computer Science & IT
CSRID (Computer Science Research and Its Development Journal) is a scientific journal published by LPPM Universitas Potensi Utama in collaboration with professional computer science associations, Indonesian Computer Electronics and Instrumentation Support Society (IndoCEISS) and CORIS (Cooperation Research Inter University).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
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Search results for , issue "Vol. 15 No. 2: June 2023" : 6 Documents clear
Implementasi Aplikasi E-Office di Badan Pendapatan Daerah Provinsi Sulawesi Utara Efraim Dahlan; Nathania Mangundap; Edson Putra; Olvie Atteng
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

In the Regional Revenue Agency of North Sulawesi Province (BAPENDA), the process of sending letters still uses the manual method. By using the manual method, letters that have been sent cannot be tracked with certainty on where the letters are. This obstacle becomes a challenge to the organization in carrying out fast and precise business processes. So, the researcher was given the task of making an E-Office application. The purpose of making the application can simplify and develop the process of sending the letter. In short, the E-Office application that was created has the aim of facilitating business processes for correspondence within BAPENDA so that it can be carried out quickly, precisely, and flexibly. This application will be made based on the letter management SOP that applies at BAPENDA. Research on required applications uses the Modified Waterfall model, which is the result of a modified Waterfall method that is more flexible than the Waterfall model. The type of data taken is qualitative data, in which data is taken using interviews with parties involved in the process of business correspondence and dispositions. Information from the interview will be recorded and used to design the application to suit the needs & desires of the organization. The E-Office application will provide a new experience for organizations in carrying out correspondence business processes with convenience such as the user being able to find out where the letter has been, sending it is also made easier because it can be done wherever the user is, as long as they have an internet connection, it also makes it easier to view file and letter history with shipping details, etc. By implementing this application, it can encourage organizations to compete with other organizations in utilizing internet technology as an intermediary for business processes.
Smart Fish Farm Budidaya Ikan Nila Menggunakan NodeMCU Terintegrasi Berbasis Internet Of Things Jeki Kuswanto Jeki Kuswanto; Muhammad Koprawir; Anggit Ferdita Nugraha
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

Fish cultivation technology combined with agriculture is developing rapidly, and many suitable systems have emerged to combine planting media and fish cultivation, one of which is viticulture planting media where this agricultural cultivation system is carried out vertically or in stages in indoor and outdoor scopes. Some processes are still carried out manually, namely watering plants, checking water PH, feeding fish, checking water temperature in ponds, and controlling soil moisture levels, this is done manually. Therefore,. This system is made automated based on IoT (internet of things) is needed to overcome some of these problems by utilizing NodeMCu as a microcontroller which will be connected to soil moisture sensors, temperature sensors, PH meters, DC motors, control and monitoring of watering plants, fish feeding, water condition of water can be done automatically. Smart fish Farm cultivating tilapia and iot (internet of things) based verticulture plants can display appropriate data via a mobile application that can be viewed by the user, starting from the soil moisture level displaying the results of pH levels from 1 to 10 pH levels and displaying pond temperature fish from vulnerable 15 to 32 degrees Celsius and mobile applications can control the fish feed system. Keywords—Internet of things, Smart fish Farm, NodeMCu, Verticulture
Modifikasi Algoritma Caesar Chiper Dengan Menambahkan Key Untuk Peningkatan Keamanan Rudolf Sinaga; Frangk
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

This article discusses the modification of the Caesar Cipher algorithm by adding a key as a way to increase its security. Caesar Cipher is one of the classic algorithms used to encrypt messages by shifting each letter in the original message 3 times, where the shift is 3 times as the key used. However, even though Caesar Cipher is relatively simple and easy to implement, this algorithm is vulnerable to brute force attacks because it only has 26 possible shift ciphers. Therefore, the authors propose a modification by adding a key to this algorithm. In this modification, keys are added to each letter of the original message before it is shifted, thus making the resulting shift patterns more complex and difficult to solve. The test results show that modifying the Caesar Cipher algorithm with the addition of a key can improve message security. However, the author also realizes that although the addition of keys can improve security, this algorithm still has other weaknesses such as being vulnerable to frequency analysis attacks. Therefore, the authors conclude that this modification can only improve Caesar Cipher's security to a certain level and still needs to be combined with other encryption techniques to achieve better security.
Deteksi Spam Bot Pada Komentar Youtube: Tinjauan Literatur Sistematis Syafrial Pane; Dzul Jalali Wal Ikram
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

YouTube is a very popular social media platform and is used by millions of people around the world. However, the presence of spam in comments can disrupt the user experience and affect the overall quality of the platform. Therefore, in this article, we conducted a Systematic Literature Review (SLR) to evaluate methods for detecting spam in comments on YouTube. In this SLR, we search for related research published between 2018 and 2023 in trusted databases such as Science Direct, IEEE Xplore, and Springer using Publish or Perish software. After making the selection, 17 of the 80 selected articles met our research criteria. The SLR results show that the Email dataset is the most widely used in spam detection research, and the most frequently used approach is supervised learning. In addition, most of the research focuses more on selecting features to improve accuracy in spam detection. The findings from this SLR can provide important insights for researchers who wish to conduct further research on spam detection on comments on YouTube.
Malware Detection pada Static Analysis Windows Portable Executable (PE) Menggunakan Support Vector Machine dan Decision Tree Mohammad Mirza Qusyairi; Rio Guntur Utomo; Rahmat Yasirandi
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

Malware has become a major issue for computer system security today. Due to its ability to spread rapidly and negatively impact system performance, malware detection becomes crucial. One of the methods for malware detection is performing classification using Machine Learning, which learns the variable values of an application without executing it. In this study, the author evaluates the method of malware detection in the static analysis of Windows Portable Executable (PE) using Support Vector Machine (SVM) and Decision Tree. The author uses a dataset of PE files related to malware and safe applications from malware Using SVM and Decision Tree algorithms to classify the PE files as malware or not, determining the best machine learning algorithm for malware detection in PE files.
Retweet Prediction Using ANN Method and Artificial Bee Colony Jondri Jondri; Kamaludin Hanif Farisi; Kemas Muslim Lhaksmana
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

In the ongoing modern era, the rapid dissemination of information takes place, utilizing various channels for data exchange. One such platform is the social media platform Twitter, renowned for its swift and extensive information propagation. A pivotal factor contributing to information distribution on Twitter is the retweet feature, whereby users can redistribute content to their audience. A study has been conducted to forecast this retweet activity by employing the Artificial Neural Network classification method in conjunction with the Artificial Bee Colony optimization approach. This study leverages diverse features, encompassing content-based feature, user-based feature, and time-based feature. The evaluation results from this study reveal that the proposed method achieves an accuracy value of around 83% with the highest accuracy value reaching 84%. These findings indicate that the fusion of the Artificial Neural Network classification method executed with optimization using the Artificial Bee Colony algorithm yields dependable and consistent performance in predicting retweet activities.

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